NEURORADIOLOGY / REVIEW PAPER
Figure from article: Magnetic Resonance Imaging...
 
KEYWORDS
TOPICS
ABSTRACT
Magnetic resonance imaging (MRI) is becoming an increasingly important tool in the diagnostic approach to Parkinson’s disease (PD), extending its role beyond the exclusion of secondary causes of parkinsonism. Recent develop­ments in high-resolution imaging techniques – including neuromelanin-sensitive MRI, susceptibility-weighted imaging, quantitative susceptibility mapping, diffusion tensor imaging, and functional MRI – have enabled in vivo assessment of substantia nigra degeneration, iron accumulation, and functional connectivity alterations. These ima­ging findings correspond to core pathophysiological mechanisms of PD and support efforts toward earlier and more precise diagnosis. This narrative review outlines the current capabilities and limitations of MRI in the context of the evolving biological definition of PD, which emphasizes the presence of pathological α-synuclein as the defining feature, regardless of clinical manifestations. We discuss the utility of MRI across different disease stages – from prodromal to advanc­ed – and its value in differentiating PD from atypical parkinsonian syndromes such as multiple system atrophy, progressive supranuclear palsy, and corticobasal degeneration. Special attention is paid to age-related diagnostic strategies, including recommendations for imaging protocols and adjunctive testing (e.g., dopamine transporter single photon emission computed tomography, positron emission tomography, genetic testing) for different age groups. We also review the role of radiomics and machine learning in enhancing diagnostic accuracy and consider practical limitations related to MRI field strength, reader expertise, and standardization. This article aims to serve as a practical primer for radiologists involved in the imaging of parkinsonian syndromes and provides a framework for integrating MRI findings into multimodal diagnostic pathways.
REFERENCES (30)
1.
Cardoso F, Goetz CG, Mestre TA, Sampaio C, Adler CH, Berg D, et al. A statement of the MDS on biological definition, staging, and classification of Parkinson’s disease. Mov Disord 2024; 39: 259-266.
 
2.
Simuni T, Chahine LM, Poston K, Brumm M, Buracchio T, Campbell M, et al. A biological definition of neuronal α-synuclein disease: towards an integrated staging system for research. The Lancet Neurology 2024; 23: 178-190.
 
3.
Madelung CF, Løkkegaard A, Fuglsang SA, Marques MM, Boer VO, Madsen KH, et al. High-resolution mapping of substantia nigra in Parkinson’s disease using 7 tesla magnetic resonance imaging. NPJ Parkinsons Dis 2025; 11: 113. DOI: 10.1038/s41531-025-00972-7.
 
4.
Bae YJ, Kim JM, Sohn CH, Choi JH, Choi BS, Song YS, et al. Imaging the substantia nigra in Parkinson disease and other parkinsonian syndromes. Radiology 2021; 300: 260-278.
 
5.
Höglinger GU, Lang AE. SynNeurGe: the road ahead for a biological definition of Parkinson’s disease. J Parkinsons Dis 2024; 15: 931-938.
 
6.
Aslam S, Manfredsson F, Stokes A, Shill H. “Advanced” Parkinson’s disease: a review. Parkinsonism Relat Disord 2024; 123: 106065. DOI: 10.1016/j.parkreldis.2024.106065.
 
7.
Langley J, Huddleston DE, Crosson B, Song DD, Factor SA, Hu X. Multimodal assessment of nigrosomal degeneration in Parkinson’s disease. Parkinsonism Relat Disord 2020; 80: 102-107.
 
8.
Guan X, Lancione M, Ayton S, Dusek P, Langkammer C, Zhang M. Neuroimaging of Parkinson’s disease by quantitative susceptibility mapping. Neuroimage 2024; 289: 120547. DOI: 10.1016/j.neuroimage.2024.120547.
 
9.
Biondetti E, Gaurav R, Yahia-Cherif L, Mangone G, Pyatigorskaya N, Valabrègue R, et al. Spatiotemporal changes in substantia nigra neuro­melanin content in Parkinson’s disease. Brain 2020; 143: 2757-2770.
 
10.
Brammerloh M, Kirilina E, Alkemade A, Bazin PL, Jantzen C, Jäger C, et al. Swallow tail sign: revisited. Radiology 2022; 305: 674-677.
 
11.
Wei X, Luo C, Li Q, Hu N, Xiao Y, Liu N, et al. White matter abnormalities in patients with Parkinson’s disease: a meta-analysis of diffusion tensor imaging using tract-based spatial statistics. Front Aging Neurosci 2021; 12: 610962. DOI: 10.3389/fnagi.2020.610962.
 
12.
Piramide N, De Micco R, Siciliano M, Silvestro M, Tessitore A. Resting-state functional MRI approaches to Parkinsonisms and related dementia. Curr Neurol Neurosci Rep 2024; 24: 461-477.
 
13.
Burciu RG, Vaillancourt DE. Imaging of motor cortex physiology in Parkinson’s disease. Mov Disord 2018; 33: 1688-1699.
 
14.
Wang X, Huang P, Haacke EM, Liu Y, Zhang Y, Jin Z, et al. Locus coeruleus and substantia nigra neuromelanin magnetic resonance imaging differentiates Parkinson’s disease and essential tremor. Neuroimage Clin 2023; 38: 103420. DOI: 10.1016/j.nicl.2023.103420.
 
15.
Wang J, Li Y, Huang Z, Wan W, Zhang Y, Wang C, et al. Neuromelanin-sensitive magnetic resonance imaging features of the substantia nigra and locus coeruleus in de novo Parkinson’s disease and its phenotypes. Eur J Neurol 2018; 25: 949-e973. DOI: 10.1111/ene.13628.
 
16.
Schwarz ST, Afzal M, Morgan PS, Bajaj N, Gowland PA, Auer DP. The ‘swallow tail’appearance of the healthy nigrosome – a new accurate test of Parkinson’s disease: a case-control and retrospective cross-sectional MRI study at 3T. PloS One 2014; 9: e93814. DOI: 10.1371/journal.pone.0093814.
 
17.
Noh Y, Sung YH, Lee J, Kim EY. Nigrosome 1 detection at 3T MRI for the diagnosis of early-stage idiopathic Parkinson disease: assessment of diagnostic accuracy and agreement on imaging asymmetry and clinical laterality. Am J Neuroradiol 2015; 36: 2010-2016.
 
18.
Hartono S, Chen RC, Welton T, Tan AS, Lee W, Teh PY, et al. Quantitative iron-neuromelanin MRI associates with motor severity in Parkinson’s disease and matches radiological disease classification. Front Aging Neurosci 2023; 15: 1287917. DOI: 10.3389/fnagi.2023.1287917.
 
19.
Tahmasian M, Bettray LM, van Eimeren T, Drzezga A, Timmermann L, Eickhoff CR, et al. A systematic review on the applications of resting-state fMRI in Parkinson’s disease: Does dopamine replacement therapy play a role? Cortex 2015; 73: 80-105.
 
20.
Höglinger GU, Adler CH, Berg D, Klein C, Outeiro TF, Poewe W, et al. A biological classification of Parkinson’s disease: the SynNeurGe research diagnostic criteria. Lancet Neurol 2024; 23: 191-204.
 
21.
Basaia S, Agosta F, Sarasso E, Balestrino R, Stojković T, Stanković I, et al. Brain connectivity networks constructed using MRI for predic­ting patterns of atrophy progression in Parkinson disease. Radiology 2024; 311: e232454. DOI: 10.1148/radiol.232454.
 
22.
Palermo G, Giannoni S, Bellini G, Siciliano G, Ceravolo R. Dopamine transporter imaging, current status of a potential biomarker: a comprehensive review. Int J Mol Sci 2021; 22: 11234. DOI: 10.3390/ijms222011234.
 
23.
Ye Q, Lin C, Xiao F, Jiang T, Hou J, Zheng Y, et al. Individualized diagnosis of Parkinson’s disease based on multivariate magnetic resonance imaging radiomics and clinical indexes. Front Aging Neurosci 2025; 17: 1504733. DOI: 10.3389/fnagi.2025.1504733.
 
24.
Shokrpour S, Moghadam Farid AM, Bazzaz Abkenar S, Haghi Kashani M, Akbari M, Sarvizadeh M. Machine learning for Parkinson’s disease: a comprehensive review of datasets, algorithms, and challenges. NPJ Parkinsons Dis 2025; 11: 187. DOI: 10.1038/s41531-025-01025-9.
 
25.
Shaban M, Amara AW. Resting-state electroencephalography based deep-learning for the detection of Parkinson’s disease. PLoS One 2022; 17: e0263159. DOI: 10.1371/journal.pone.0263159.
 
26.
Huppertz HJ, KrollSeger J, Klöppel S, Ganz RE, Kassubek J. Differentiation of neurodegenerative parkinsonian syndromes by volumetric magnetic resonance imaging analysis and support vector machine classification. Mov Disord 2016; 31: 1506-1517.
 
27.
Spiegel C, Siejka TP, Marotta C, Lee JJ, Bertram K, O’Brien TJ, et al. Brainstem and cerebellar volume loss and the associated clinical features in progressive supranuclear palsy. medRxiv 2025. DOI: 10.1101/2025.07.06.25330975.
 
28.
Josephs KA, Whitwell JL, Boeve BF, Knopman DS, Petersen RC, Hu WT, et al. Anatomical differences between CBS-corticobasal degeneration and CBS-Alzheimer’s disease. Mov Disord 2010; 25: 1246-1252.
 
29.
Ishii K. Diagnostic imaging of dementia with Lewy bodies, frontotemporal lobar degeneration, and normal pressure hydrocephalus. Jpn J Radiol 2020; 38: 64-76.
 
30.
Mitchell T, Wilkes BJ, Archer DB, Chu WT, Coombes SA, Lai S, et al. Advanced diffusion imaging to track progression in Parkinson’s disease, multiple system atrophy, and progressive supranuclear palsy. Neuromage Clin 2022; 34: 103022. DOI: 10.1016/j.nicl.2022.103022.
 
ISSN:1899-0967
Journals System - logo
Scroll to top